Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns

Panagiotis D. Ritsos; Saiful Khan; Scott Jones; Benjamin Bach; Julie Meikle; Jonathan C. Roberts; Jo Wood; Min Chen

Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns

Panagiotis D. Ritsos, Saiful Khan, Scott Jones, Benjamin Bach, Julie Meikle, Jonathan C. Roberts, Jo Wood, Min Chen

School of Computer Science & Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this bulletin video, we summarize a novel technique for authoring storytelling visualization [3–5]. The technique was developed by one of the teams in the RAMPVIS project [1, 2], which provided visualization support to epidemiological modeling during the COVID-19 pandemic. The team explored the prevailing approaches,
in the UK and internationally, for creating public-facing visualizations related to the pandemic. This ranged from those produced by a number of governments (e.g., the four home nations in the UK), organizations (e.g., WHO, UK ONS), universities (e.g., Johns Hopkins dashboards), media outlets (e.g., FT Coronavirus tracker),
and non-commercial web services (e.g., Worldometers). The team concluded that we should complement, but not duplicate, the existing effort, and defined our goal as to inform the public through advanced storytelling visualization.

Original language	English
Title of host publication	IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes)
Publisher	IEEE
Publication status	Published - Oct 2023
Event	IEEE VIS: Visualization & Visual Analytics: IEEE VIS 2023 - Melbourne Convention and Exhibition Centre, Melbourne, Australia Duration: 22 Oct 2023 → 27 Oct 2023 https://ieeevis.org/year/2023/welcome

Conference

Conference	IEEE VIS: Visualization & Visual Analytics
Abbreviated title	IEEE VIS
Country/Territory	Australia
City	Melbourne
Period	22/10/23 → 27/10/23
Internet address	https://ieeevis.org/year/2023/welcome

Keywords

Visualization
Visual Analytics
COVID-19 responses
data patterns
storytelling
volunteering operation

Cite this

@inproceedings{98076e42967a46f38eaf92919f0d8504,

title = "Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns",

abstract = "In this bulletin video, we summarize a novel technique for authoring storytelling visualization [3–5]. The technique was developed by one of the teams in the RAMPVIS project [1, 2], which provided visualization support to epidemiological modeling during the COVID-19 pandemic. The team explored the prevailing approaches,in the UK and internationally, for creating public-facing visualizations related to the pandemic. This ranged from those produced by a number of governments (e.g., the four home nations in the UK), organizations (e.g., WHO, UK ONS), universities (e.g., Johns Hopkins dashboards), media outlets (e.g., FT Coronavirus tracker),and non-commercial web services (e.g., Worldometers). The team concluded that we should complement, but not duplicate, the existing effort, and defined our goal as to inform the public through advanced storytelling visualization.",

keywords = "Visualization, Visual Analytics, COVID-19 responses, data patterns, storytelling, volunteering operation",

author = "Ritsos, \{Panagiotis D.\} and Saiful Khan and Scott Jones and Benjamin Bach and Julie Meikle and Roberts, \{Jonathan C.\} and Jo Wood and Min Chen",

year = "2023",

month = oct,

language = "English",

booktitle = "IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes)",

publisher = "IEEE",

note = "IEEE VIS: Visualization \& Visual Analytics : IEEE VIS 2023, IEEE VIS ; Conference date: 22-10-2023 Through 27-10-2023",

url = "https://ieeevis.org/year/2023/welcome",

}

Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns. / Ritsos, Panagiotis D.; Khan, Saiful; Jones, Scott et al.
IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes). IEEE, 2023.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns

AU - Ritsos, Panagiotis D.

AU - Khan, Saiful

AU - Jones, Scott

AU - Bach, Benjamin

AU - Meikle, Julie

AU - Roberts, Jonathan C.

AU - Wood, Jo

AU - Chen, Min

PY - 2023/10

Y1 - 2023/10

N2 - In this bulletin video, we summarize a novel technique for authoring storytelling visualization [3–5]. The technique was developed by one of the teams in the RAMPVIS project [1, 2], which provided visualization support to epidemiological modeling during the COVID-19 pandemic. The team explored the prevailing approaches,in the UK and internationally, for creating public-facing visualizations related to the pandemic. This ranged from those produced by a number of governments (e.g., the four home nations in the UK), organizations (e.g., WHO, UK ONS), universities (e.g., Johns Hopkins dashboards), media outlets (e.g., FT Coronavirus tracker),and non-commercial web services (e.g., Worldometers). The team concluded that we should complement, but not duplicate, the existing effort, and defined our goal as to inform the public through advanced storytelling visualization.

AB - In this bulletin video, we summarize a novel technique for authoring storytelling visualization [3–5]. The technique was developed by one of the teams in the RAMPVIS project [1, 2], which provided visualization support to epidemiological modeling during the COVID-19 pandemic. The team explored the prevailing approaches,in the UK and internationally, for creating public-facing visualizations related to the pandemic. This ranged from those produced by a number of governments (e.g., the four home nations in the UK), organizations (e.g., WHO, UK ONS), universities (e.g., Johns Hopkins dashboards), media outlets (e.g., FT Coronavirus tracker),and non-commercial web services (e.g., Worldometers). The team concluded that we should complement, but not duplicate, the existing effort, and defined our goal as to inform the public through advanced storytelling visualization.

KW - Visualization

KW - Visual Analytics

KW - COVID-19 responses

KW - data patterns

KW - storytelling

KW - volunteering operation

UR - https://vis4pandemres.github.io/bulletins/

M3 - Conference contribution

BT - IEEE VIS Workshop on Visualization for Pandemic and Emergency Responses 2023 (Vis4PandEmRes)

PB - IEEE

T2 - IEEE VIS: Visualization & Visual Analytics

Y2 - 22 October 2023 through 27 October 2023

ER -

Creating storytelling visualizations for the Covid-19 pandemic using Feature-Action Design Patterns

Abstract

Conference

Keywords

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